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Integrated Sequential Groundwater Contaminant Source Characterization and Pareto-Optimal Monitoring Network Design Application for a Contaminated Aquifer Site

机译:污染含水层场地地下水污染物源序贯表征与帕累托最优监测网络设计应用

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摘要

Accurate and reliable groundwater contaminant source characterization with limited contaminant concentration monitoring measurement data remains a challenging problem. This study presents an illustrative application of developed methodologies to a real-life contaminated aquifer. The source characterization and optimal monitoring network design methodologies are used sequentially for a contaminated aquifer site located in New South Wales, Australia. Performance of the integrated optimal source characterization methodology combining linked simulation-optimization, fractal singularity mapping technique (FSMT) and Pareto optimal solutions is evaluated. This study presents an integrated application of optimal source characterization with spatiotemporal concentration measurement data obtained from sequentially designed monitoring networks. The proposed sequential source characterization and monitoring network design methodology shows efficiency in identifying the unknown source characteristics. The designed monitoring network achieves comparable efficiency and accuracy utilizing much smaller number of monitoring locations as compared to a more ideal scenario where concentration measurements from a very large number of widespread monitoring wells are available. The proposed methodology is potentially useful for efficient characterization of unknown contaminant sources in a complex contaminated aquifer site, where very little initial concentration measurement data are available. The illustrative application of the methodology to a real-life contaminated aquifer site demonstrates the capability and efficiency of the proposed methodology.
机译:准确可靠的地下水污染物源表征和有限的污染物浓度监测测量数据仍然是一个具有挑战性的问题。本研究说明了已开发方法在现实生活中受污染含水层中的应用。对位于澳大利亚新南威尔士州的污染含水层场址依次采用源表征和最佳监测网络设计方法。评估了结合链接模拟优化、分形奇点映射技术(FSMT)和帕累托最优解的集成最优源表征方法的性能。本研究提出了一种最佳源表征的综合应用,该应用利用从顺序设计的监测网络获得的时空浓度测量数据。所提出的序列源表征和监测网络设计方法在识别未知源特征方面表现出了效率。与更理想的场景相比,所设计的监测网络利用更少的监测位置实现了相当的效率和准确性,在更理想的场景中,可以从大量广泛的监测井中进行浓度测量。所提出的方法可能有助于在复杂的受污染含水层场地中有效表征未知污染源,因为那里的初始浓度测量数据很少。该方法在现实生活中受污染的含水层场址的说明性应用表明了所提出的方法的能力和效率。

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